A thought for the day. Stick with me on this, I'm still deciding if there's something in it: I will only know after I've published it though so here goes.

I'm musing about this visualisation work that has received a lot of love and attention on blogs and social media over the past few days. Created by the excellent people in the Wall Street Journal graphics team, it portrays data about the impact of vaccines in battling infectious diseases in the 20th Century.

The chart that has had the most impact, due to the highly topical nature of its subject, is the measles chart. This was certainly the image that was drew me in and was used to accompany the many positive tweets it received.

My question is this: do we like the visualisation or do we like the data?

I have a few questions about the colour scheme - it is not explained what the implied threshold of the blue >> green colour means - but it is an attractive looking chart and, in using a heatmap, a suitable choice to display this data. And what a story we see! The shape of the data after the introduction of the vaccine wonderfully demonstrates evidence of its success.

Unquestionably, the visualisation reveals the findings from the data very clearly. However - and this is not a criticism whatsoever - other visualisation approaches would also have revealed this pattern (albeit most would only show an overall pattern than perhaps a state resolution). I would even maybe dare to suggest that the numbers are so compelling that you would 'see' the bigger picture of reduction even in a table of raw data.

So, that question again, but framed more broadly. When we like a visualisation like this is it because it is the best way, maybe even the only way, to show a certain pattern in data OR are we actually so engaged because the data that sits beneath the visual has a clear causal relationship between an action and its effect over time - the holy grail of analysis!

What if there was no sudden drop, as shown in the crudely photoshopped version below? Is the visualisation - the design layer - still of merit? Of course you probably wouldn't produce the visualisation in the first place but, having lost that wonderfully clear reduction in the measle cases in the data layer, does it change our view of the design layer?

I guess it depends on your perspective and what you're seeking to understand. Yes, I know that's criminally boring but it is true. If you are pro or anti-vax will certainly influence your stand point on the findings but I'm kind of interested in going beyond those subject matter biases to think about how we evaluate a visualisation's merits.

Sometimes in workshops, in one of my early class exercises, I might find myself lavishing praise on a visualisation work based on certain design features. Yet the delegates in the room, who haven't at that stage necessarily developed such a forensic lens, are more underwhelmed by what they are seeing. They are looking through and beyond that visual surface at the patterns of data beneath and are maybe not getting much from it. It is almost like I'm so concerned with assessing the choice and quality of glass in a window I ignore the view beyond.

As a visualisation practitioner, I am often so more concerned with design choices that I rarely find myself looking beneath the design surface. For example, the discovery I treasure most from this project is the super hover action when your cursor sits above the heat map cells and a little marker appears on the colour scale to assist in reading the value. I've not seen (or noticed) that device being used before and think it is a brilliant little idea. Measles is going down? Yeah, great, but have you seen the hover marker!

I've run out of muse-momentum now so I'll put down my pipe, and do something else other than contemplating life whilst staring out of the window. Or maybe at it.

7 responses to “Is it the visualisation or the data we like?”

Andy, there is a problem when we fall in love only with the visualization, when we should fall in love also with the data (hi Enrico!). This one is interesting, impressive, pretty but also redundant and not very precise due to color coding. I would prefer a line chart, but I’m sure this one would be much improved just by using a different sorting key, allowing us to see other patterns and not only the sudden drop.

So, there must be a perfect love triangle (me, the visuals and the data), where everyone loves everyone! 🙂

I agree with Jorge.
The measure is whether the visualisation has the desired impact. In this case, I’d guess the impact question is: “Do people have a clearer understanding of the impact of vaccination?”

The answer is most certainly yes for this viz.

The data is very visually clear and there’s also a slight novelty in the way this is being displayed; that piques peoples’ interest too.

The visualisation doesn’t work with dull data. We like the visuslisation because the data fits it well.

Jorge says he would prefer a line chart. Well, that would be less novel and thus less engaging.

Interesting questions/discussion Andy! I think in the case of vaccination data, it’s probably the data itself that I’m most impressed and fascinated by. It’s so compelling that, honestly, any number of charting techniques could have been employed.

Speaking of techniques, this particular visualization does some things well, but I’m not completely convinced that it does them well because of its design – I think it’s because the trends in vaccination data are so dramatic. I agree with Jorge in that I’d love to see this in a simpler form, one where I don’t have to decode based on color. I’d also love to be able to compare states more easily, but of course, this may not have been the designers intent. Even so, it would have been great to take the analysis one step further.

In the end I really appreciated the interactivity, not just because it allows users to see the actual data, but because it helped dispel some confusion re: the labeling of the y axis (a hurdle for anyone looking for a particular state).

All in all, a great effort by the folks at the WSJ. Of course, if they had done a line chart, we probably wouldn’t be talking about it.

Along with most everyone else, I think this measles heatmap does an excellent job of showing the dramatic change in measles cases.

However, I think it’s worth noting that the WSJ designers made a decision to present the measles chart among similar charts about other diseases. In that context, the color-based heatmap loses its effectiveness, and even becomes slightly misleading. Take a look at all 7 charts together: they all use the same color scheme, going from white to dark red. But for each chart, look at the number that dark red represents: 4000, 300, 600, 1000, 200, 300, 250!

When I first looked at the entire page, of course I spent a lot of time examining the measles chart. Then I worked my way through the others. I initially made the reasonable assumption that the charts could be “read in the same way”. So I was quite surprised when the final chart “told me” that smallpox was a huge problem in Montana as late as 1937! Only then did I look at the scales and understand the design. In the smallpox chart, dark red could mean 157 cases, while in the measles chart, a very similar color would mean 2974 cases!

You have to do a lot of mental recalibration to read all the charts on the same page and understand what each of them is saying. Because of this problem with the heatmap, I think it would have been clearer for the numbers to be presented as line charts, since the viewer could then understand the total number of cases for each disease, along with the degree of change after vaccination became available. However, I think the ideal scenario would have been to just present the highly-engaging measles heatmap on its own.

The clearness in your post is simply col and i cann assume yyou are an expert on this subject.
Fine with your permission alow me to grab your RSS feed to keep updated with forthcoming post.
Thanks a million and please keerp up the enjoyable work.

Cookie Statement

This website makes minimal use of cookies. The only cookie currently in use is used to support analysis
and understanding of how people use the website (what they like most, when is the busiest time of day on
the site, have people found new content when it is published, etc.). This analysis is performed to help
improve the content and effectiveness of the website. The data collection and reporting behind this
analysis is provided by Google Analytics (3rd party). Your continued use of this website will indicate
your agreement to the use of this cookie. You can find out more about Google Analytics’ Cookies here:
https://support.google.com/analytics/answer/6004245.